An efficient IP approach to constrained multiple face tracking and recognition

Andre Cohen, Vladimir Pavlovic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Tracking and recognition of objects, such as faces, in video is commonly accomplished in independent fashion. However, important information is contained in both problems that could be used to increase the overall recognition accuracy. We propose a unified integer program (IP) based framework for multi-object tracking and recognition in video, where the two tasks are conducted jointly, using a set of natural constraints. In the domain of multiple face recognition, pairing constraints limit the number of objects that can be labeled with the same identity while temporal constraints allow the important information about objects identities's to be used to improve tracking. Despite its appeal, the solving the IP objective can be inefficient in real-world scenarios. For this reason, we employ an approximate Generalized Assignment Problem (GAP) solution to the IP problem, which is both theoretically appealing and computationally highly efficient. We finally demonstrate that the IP and GAP methods of conducting multi-object tracking and recognition can be successfully applied to real world videos where the traditional methods of conducting tracking and recognition separately fail to produce satisfactory results.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Pages852-859
Number of pages8
DOIs
StatePublished - Dec 1 2011
Event2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011 - Barcelona, Spain
Duration: Nov 6 2011Nov 13 2011

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
CountrySpain
CityBarcelona
Period11/6/1111/13/11

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'An efficient IP approach to constrained multiple face tracking and recognition'. Together they form a unique fingerprint.

  • Cite this

    Cohen, A., & Pavlovic, V. (2011). An efficient IP approach to constrained multiple face tracking and recognition. In 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011 (pp. 852-859). [6130341] (Proceedings of the IEEE International Conference on Computer Vision). https://doi.org/10.1109/ICCVW.2011.6130341